Abstract
In this paper we address two major challenges presented by stochastic discrete optimisation problems: the multiobjective nature of the problems, once risk aversion is incorporated, and the frequent difficulties in computing exactly, or even approximately, the objective function. The latter has often been handled with methods involving sample average approximation, where a random sample is generated so that population parameters may be estimated from sample statistics-usually the expected value is estimated from the sample average. We propose the use of multiobjective metaheuristics to deal with these difficulties, and apply a multiobjective local search metaheuristic to both exact and sample approximation versions of a mean-risk static stochastic knapsack problem. Variance and conditional value-at-risk are considered as risk measures. Results of a computational study are presented, that indicate the approach is capable of producing high-quality approximations to the efficient sets, with a modest computational effort.

Abstract
This paper proposes a new method to manage the use of ontologies in the context of Virtual Organisations Breeding Environments (VBEs). The research focuses on the dissolution phase of a Virtual Enterprise (VE), where ontology decomposition techniques are used to enrich the ontology library. First, an overview of the process used and the Ontology Library System (OLS) adopted are described. Then, the ontologies' ranking and classification method are described, explaining a set of metrics inspired by social network approaches. Finally, the composition method used to construct a global ontology and the decomposition algorithm implemented to segment an ontology are presented. Copyright © 2010 Inderscience Enterprises Ltd.

Abstract
This paper describes an approach and an implementation for the semantic integration of social and domain ontologies in a collaborative platform. The platform, built based on the Drupal CMS framework, aims to offer SMEs possibilities to access specific knowledge by means of a collaborative community. A model to semantically express the socio-collaborative activities of the platform connected with the domain knowledge related to the project is presented. The model is based on existing W3C ontologies such as FOAF, SIOC and SIOC-types for the socio-collaborative semantics and SKOS to describe the domain knowledge. An architecture to support the model and related applications of the semantic metadata generated in the platform are also described.

Abstract
Looking at collaborative networks of organizations as social-technical systems, information and knowledge sharing implies sharing a set of common conceptual structures across organizations. Through this paper, we describe a case study on how to construct meaningful collective conceptualizations by means of a new approach based on conceptual blending theory.

Abstract
This paper describes an approach to the design of performance management models in collaborative networks, from a constructivist approach. The general approach is outlined and the part concerning a multi-criteria decision support method is explained. The paper finishes with an illustration of a scenario for test and validation of the method.

Abstract
The process of collective development of conceptual models has not been satisfactorily addressed in the knowledge representation research literature. Nevertheless, a shared conceptualization of a given reality is the cornerstone to build semantic artifacts such as ontologies. This paper presents a new platform that implements the Col Blend method, designed to support a collaborative conceptualization process. The platform is based on semantic technologies and proposes a set of functionalities for importing, creating, manipulating, discussing and documenting conceptual models that can act e.g., as the specification of a formal ontology. The platform is being tested and used in two research projects(1).